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Learner Reviews & Feedback for Fundamentals of Reinforcement Learning by University of Alberta

2,183 ratings
532 reviews

About the Course

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces you to the fundamentals of Reinforcement Learning. When you finish this course, you will: - Formalize problems as Markov Decision Processes - Understand basic exploration methods and the exploration/exploitation tradeoff - Understand value functions, as a general-purpose tool for optimal decision-making - Know how to implement dynamic programming as an efficient solution approach to an industrial control problem This course teaches you the key concepts of Reinforcement Learning, underlying classic and modern algorithms in RL. After completing this course, you will be able to start using RL for real problems, where you have or can specify the MDP. This is the first course of the Reinforcement Learning Specialization....

Top reviews

Jul 6, 2020

An excellent introduction to Reinforcement Learning, accompanied by a well-organized & informative handbook. I definitely recommend this course to have a strong foundation in Reinforcement Learning.

Apr 7, 2020

This course is one of the best I've learned so far in coursera. The explanations are clear and concise enough. It took a while for me to understand Bellman equation but when I did, it felt amazing!

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326 - 350 of 533 Reviews for Fundamentals of Reinforcement Learning

By Antonio P

Nov 11, 2019

Great introductional course on Reinforcement Learning

By Gyanendra D D

Dec 11, 2020

Very good course if you follow along with the book.

By Chirag M

Nov 5, 2020

Great course! A lot of good material and insights!

By Jingxin X

May 17, 2020

Very helpful hands-on experience with the notebooks

By Yue Z

Feb 9, 2020

Everything is good except the peer review question.

By Tobias K

Sep 24, 2021

G​reat mixture of theory and the intuition behind!

By Jaime C

Mar 27, 2021

Excellent, good combination of theory and practice

By Mario A C S

Oct 16, 2020

Excellent course, great materials and explanations

By Mark P

May 19, 2020

Excellent intro. Well paced, clear videos. Thanks!

By Pratyush M

Jun 15, 2020

some more practical implementation can be better.

By Maria D

May 23, 2020

Challenging but helpful, awesome practical tasks!

By Deleted A

Sep 6, 2019

Builds a good foundation of basic concepts of RL.

By Marco G

Jan 7, 2021

clearly explained, nice textbook, good exercises

By Sriram R

Aug 24, 2019

Well organized course. Good pedagogy. Well done!

By Dongyu L

May 20, 2021

Very good and clear introduction of the course.

By Shamuwel A A

Nov 24, 2020

Fantastic beginning to a a very exciting topic.

By Tuyên Đ

Aug 24, 2020

perfect for who want to getting started with RL

By Debadri B

May 29, 2020

Very good course for understanding basics of RL

By Xiyu Z

Aug 13, 2021

Great! I never learnt it so clearly in school.

By Charles X

Jun 19, 2021

Very good one to get familiar with Q-learning.

By Eduardo F d S

Jul 26, 2020

Good material and very well organized. Thanks!

By Sandro A

Mar 23, 2020

Great introduction to Reinforcement Learning!!

By Kyle W

Feb 16, 2020

I enjoy the programming assignments very much.

By Alejandro D

Aug 11, 2019

Excellent! Great content and delivery quality.

By Kyle N

Aug 15, 2019

great course!! thanks Adam, Martha and team!!